code: def forward(self, q, k, v):
      n, device, scale = q.shape[-2], q.device, q.shape[-1] ** -0.5
  
      if self.use_flash:
          return self.flash_attn(q, k, v)
  
      # similarity
  
      sim = einsum("b h i d, b j d -> b h i j", q, k) * scale
  
      # attention
  
      attn = sim.softmax(dim=-1)
  
      # aggregate values
  
      out = einsum("b h i j, b j d -> b h i d", attn, v)
  
      return out
  
imports: from collections import namedtuple
  from packaging import version
  import torch
  import torch.nn.functional
  from torch import nn
  from einops import rearrange
  from einops.layers.torch import Rearrange
label_desc: Use image node_id 3 for calling the Attend obj's underlying member method code with example usage: obj.forward(q, k, v) and returns: out, self